Robots Dynamics: Application and Control

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: closed (20 September 2022) | Viewed by 32509

Special Issue Editors

School of Industrial Engineering, Technical University of Catalonia (UPC, BarcelonaTech), E-08028 Barcelona, Spain
Interests: robotic control; system dynamics; industrial robots control and planning; autonomous robots; robot navigation; sensors in robotics
Special Issues, Collections and Topics in MDPI journals
Automatic Control Dept, Tehcnical University of Catalonia, UPC, Pau Gargallo, 14, 08028 Barcelona, Spain
Interests: automatic control; adaptive control; robust control; non-linear control; LPV systems; robot control; dynamic system modeling; simulation of dynamic systems; industrial robotics; mobile robotics

Special Issue Information

Dear Colleagues,

I would like to invite you to submit a contribution to a Special Issue of Applied Sciences entitled ‘Robots Dynamics: Application and Control’.

Robotics is a growing area applied to many fields, and the precise, accurate control of robots is necessary to have a reliable device or teams of devices to operate. In this Special Issue, authors can submit research and application works devoted to such control, with special emphasis given to the dynamics of the robots. Classical techniques can be combined with new control techniques to solve the present needs in industry. Moreover, robots are also deployed in cities, collaborating with people to share tasks—in this case, the control of the robot in contact with humans is very important and requires high reliability. These robots can have different morphologies that will require specific control techniques. Papers about unmanned surface robots, unmanned aerial robots and underwater robots and their control will be accepted in this Special Issue. The modeling and simulation of robotic platforms, fleets of robots and robots in human environments is a crucial step before deployment, and research papers in this area are also welcome in this Special Issue.

Adopting multi-, inter-, and trans-disciplinary perspectives and a systems approach, expected submissions will cover the following topics:

  1. Dynamic control in robotic systems
  2. Control systems for unmanned aerial vehicles
  3. SCLAM: simultaneous control localization and mapping
  4. State and parameter/model estimation
  5. Advanced, predictive, and optimal control for robots
  6. Visual-servoing control
  7. Fault diagnosis and detection in robotic systems
  8. Robotics modeling and simulation
  9. Robust control in robotic systems
  10. Grasping control
  11. Industrial robotics
  12. Control of collaborative robots
  13. Mobile robots in dynamic environments
  14. Tools for control implementation in robotics
  15. Robotic applications

All original articles, case reports, and review articles will be welcome.

Prof. Dr. Antoni Grau
Prof. Dr. Yolanda Bolea
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Dynamic systems
  • mobile robots
  • UAV control
  • robust control
  • visual-servoing
  • adaptive control
  • predictive control in robotics
  • modeling and simulation of robotic systems

Published Papers (12 papers)

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Research

Jump to: Review

22 pages, 8120 KiB  
Article
ROS-Based Condition Monitoring Architecture Enabling Automatic Faults Detection in Industrial Collaborative Robots
by Giacomo Nabissi, Sauro Longhi and Andrea Bonci
Appl. Sci. 2023, 13(1), 143; https://0-doi-org.brum.beds.ac.uk/10.3390/app13010143 - 22 Dec 2022
Cited by 4 | Viewed by 2597
Abstract
The Condition Monitoring (CM) of industrial collaborative robots (cobots) has the potential to decrease downtimes in highly automated production systems. However, in such complex systems, defining a strategy for effective CM and automatically detecting failures is not straightforward. In this paper, common issues [...] Read more.
The Condition Monitoring (CM) of industrial collaborative robots (cobots) has the potential to decrease downtimes in highly automated production systems. However, in such complex systems, defining a strategy for effective CM and automatically detecting failures is not straightforward. In this paper, common issues related to the application of CM to collaborative manipulators are first introduced, discussed, and then, a solution based on the Robot Operating System (ROS) is proposed. The content of this document is highly oriented towards applied research and the novelty of this work mainly lies in the proposed CM architecture, while the methodology chosen to assess the manipulator’s health is based on previous research content. The CM architecture developed and the relative strategy used to process data are useful for the definition of algorithms for the automatic detection of failures. The approach is based on data labeling and indexing and aims to extract comparable data units to easily detect possible failure. The end of this paper is provided with a proof of concept (PoC) applied to an industrial collaborative manipulator where the proposed CM strategy has been implemented and tested in a real application scenario. Finally, it is shown how the proposed methodology enables the possibility of defining standard Health Indicators (HIs) to detect joint anomalies using torque information even under a highly dynamic and non-stationary environmental conditions. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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10 pages, 1136 KiB  
Communication
State Observer Based on an Accelerometer for an Elastic Joint with Nonlinear Friction
by Kwang-Hee Lee, Hyungjong Kim and Tae-Yong Kuc
Appl. Sci. 2022, 12(24), 12991; https://0-doi-org.brum.beds.ac.uk/10.3390/app122412991 - 18 Dec 2022
Cited by 1 | Viewed by 1040
Abstract
This paper presents a state observer for an elastic joint with nonlinear friction via the information from an acceleration sensor. In order to avoid discontinuities, the nonlinear friction of the motor, which includes static, coulomb, and viscous terms, is considered a smooth function. [...] Read more.
This paper presents a state observer for an elastic joint with nonlinear friction via the information from an acceleration sensor. In order to avoid discontinuities, the nonlinear friction of the motor, which includes static, coulomb, and viscous terms, is considered a smooth function. In addition, it uses an acceleration sensor to obtain the information about the link with high uncertainty. The proposed state observer guarantees that the estimation error for the position and velocity of the link connected via an elastic joint containing a nonlinear stiffness (elasticity) converges to zero. In addition, it is shown that the observer gain can be designed by LMI (linear matrix inequality) optimization. Finally, to verify the performance of the proposed observer, the method proposed in this paper is tested by experiments on a two-inertia system with an elastic shaft. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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22 pages, 2140 KiB  
Article
A Robust H Application for Motor-Link Control Systems of Industrial Manipulators
by Marina Indri, Martina Bellissimo, Stefano Pesce and Valerio Perna
Appl. Sci. 2022, 12(17), 8890; https://0-doi-org.brum.beds.ac.uk/10.3390/app12178890 - 05 Sep 2022
Cited by 3 | Viewed by 1207
Abstract
H control approaches are widely investigated in various application fields and in the robotics area, too, for their robustness properties. However, they are still rarely adopted in the industrial context for the control of robot manipulators, mainly due to the lack of [...] Read more.
H control approaches are widely investigated in various application fields and in the robotics area, too, for their robustness properties. However, they are still rarely adopted in the industrial context for the control of robot manipulators, mainly due to the lack of predefined procedures to build weighting functions able to automatically guarantee the fulfillment of the control objectives. This paper reports the first results of an academic–industrial research activity aimed at investigating the adoption of an H approach in the control software architecture of industrial manipulators, equipped with standard sensors on the motor side only. The design of the control system for a single-axis of an industrial manipulator is developed, showing that the construction of the weighting functions according to standard procedures can provide a satisfying behavior only on the motor side, leaving unacceptable oscillations of the link. A different procedure is then developed for the definition of the weighting functions with the specific aim of eliminating the possible vibrations of the mechanical structure. The proposed new form of such functions, including the main dynamic characteristics of the plant, ensures a robust, satisfying behavior on both the motor and the link side, as proven by simulation and experimental results. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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24 pages, 11022 KiB  
Article
Water Surface and Ground Control of a Small Cross-Domain Robot Based on Fast Line-of-Sight Algorithm and Adaptive Sliding Mode Integral Barrier Control
by Ke Wang, Yong Liu, Chengwei Huang and Peng Cheng
Appl. Sci. 2022, 12(12), 5935; https://0-doi-org.brum.beds.ac.uk/10.3390/app12125935 - 10 Jun 2022
Cited by 1 | Viewed by 1152
Abstract
This paper focuses on the control method of small cross-domain robots (CDR) on the water surface and the ground. The maximum size of the robot is 85 cm and the weight of the robot is 6.5 kg. To solve the problem that CDRs [...] Read more.
This paper focuses on the control method of small cross-domain robots (CDR) on the water surface and the ground. The maximum size of the robot is 85 cm and the weight of the robot is 6.5 kg. To solve the problem that CDRs cannot handle the lateral velocity, which leads to error in tracking the desired trajectory, a fast line of sight (FLOS) algorithm is proposed. In this method, an exponential term is introduced to plan the yaw angle, and a fast-extended state observer (FESO) is designed to observe the side slip angle without small angle assumption. The performances and working environments of CDRs are different on the ground and the water surface. Therefore, to avoid the driver saturation and putting risk, an adaptive sliding mode integral barrier control (ASMIBC) is proposed to constrain the robot state. This control method solves the constraint failure of the traditional integral barrier control (IBC) when the desired state is a constant. The gain of the sliding mode is adaptively adjusted by the error between the limit state and the actual state. In addition, the adaptive rate is designed for uncertain time-varying lumped disturbances, such as water resistance, currents and wind. Simulation results demonstrate the effectiveness of the proposed control method. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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19 pages, 6325 KiB  
Article
A Method for Detecting Dynamic Objects Using 2D LiDAR Based on Scan Matching
by Michal Mihálik, Marian Hruboš, Peter Vestenický, Peter Holečko, Dušan Nemec, Branislav Malobický and Ján Mihálik
Appl. Sci. 2022, 12(11), 5641; https://0-doi-org.brum.beds.ac.uk/10.3390/app12115641 - 01 Jun 2022
Cited by 5 | Viewed by 2581
Abstract
The autonomous movement of the mobile robotic system is a complex problem. If there are dynamic objects in the space when performing this task, the complexity of the solution increases. To avoid collisions, it is necessary to implement a suitable detection algorithm and [...] Read more.
The autonomous movement of the mobile robotic system is a complex problem. If there are dynamic objects in the space when performing this task, the complexity of the solution increases. To avoid collisions, it is necessary to implement a suitable detection algorithm and adjust the trajectory of the robotic system. This work deals with the design of a method for the detection of dynamic objects; based on the outputs of this method, the moving trajectory of the robotic system is modified. The method is based on the SegMatch algorithm, which is based on the scan matching, while the main sensor of the environment is a 2D LiDAR. This method is successfully implemented in an autonomous mobile robotic system, the aim of which is to perform active simultaneous localization and mapping. The result is a collision-free transition through a mapped environment. Matlab is used as the main software tool. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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24 pages, 5603 KiB  
Article
Impedance Control of Space Robot On-Orbit Insertion and Extraction Based on Prescribed Performance Method
by Dongbo Liu, Haiping Ai and Li Chen
Appl. Sci. 2022, 12(10), 5147; https://0-doi-org.brum.beds.ac.uk/10.3390/app12105147 - 19 May 2022
Cited by 2 | Viewed by 1170
Abstract
Aiming at the force position control problem of the on-orbit insertion and extraction operation of the free-floating space robot, the system dynamics model is established. According to the interaction between the end of manipulator and the environment, the second-order impedance model is established. [...] Read more.
Aiming at the force position control problem of the on-orbit insertion and extraction operation of the free-floating space robot, the system dynamics model is established. According to the interaction between the end of manipulator and the environment, the second-order impedance model is established. In order to improves the calculation efficiency, the above models are reconstructed to avoid the use of acceleration signal by introducing filtering operation. This is also conducive to the application of robot actual control. Then, an estimator requiring only the system inertia matrix is designed to compensate the modeling uncertainty, external bounded disturbance and impact effect in the process of inserting and extracting. Its structure is simple and reliable. Only one control parameter needs to be adjusted, which greatly reduces the amount of calculation. Considering that the on-orbit operation of insertion and extraction is a kind of precision operation, its control system needs to have a high-quality control performance. By introducing the prescribed performance method, the tracking error is constrained within the given range and to ensure the transient performance and steady-state performance of the control system is ensured. Finally, three simulation conditions are designed, and the results are presented to verify that the proposed algorithm has a faster convergence speed compared with traditional sliding mode controller. It can achieve vertically inserting and accurate force tracking of the manipulator end. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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23 pages, 7452 KiB  
Article
Deep Reinforcement Learning-Based Adaptive Controller for Trajectory Tracking and Altitude Control of an Aerial Robot
by Ali Barzegar and Deok-Jin Lee
Appl. Sci. 2022, 12(9), 4764; https://0-doi-org.brum.beds.ac.uk/10.3390/app12094764 - 09 May 2022
Cited by 8 | Viewed by 2964
Abstract
This research study presents a new adaptive attitude and altitude controller for an aerial robot. The proposed controlling approach employs a reinforcement learning-based algorithm to actively estimate the controller parameters of the aerial robot. In dealing with highly nonlinear systems and parameter uncertainty, [...] Read more.
This research study presents a new adaptive attitude and altitude controller for an aerial robot. The proposed controlling approach employs a reinforcement learning-based algorithm to actively estimate the controller parameters of the aerial robot. In dealing with highly nonlinear systems and parameter uncertainty, the proposed RL-based adaptive control algorithm has advantages over some types of standard control approaches. When compared to the conventional proportional integral derivative (PID) controllers, the results of the numerical simulation demonstrate the effectiveness of this intelligent control strategy, which can improve the control performance of the whole system, resulting in accurate trajectory tracking and altitude control of the vehicle. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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13 pages, 3039 KiB  
Article
Numerical Quantification of Controllability in the Null Space for Redundant Manipulators
by Seonwoo Kim, Seongseop Yun and Dongjun Shin
Appl. Sci. 2021, 11(13), 6190; https://0-doi-org.brum.beds.ac.uk/10.3390/app11136190 - 03 Jul 2021
Cited by 3 | Viewed by 2585
Abstract
Redundant motion, which is possible when robotic manipulators are over-actuated, can be used to control robot arms for a wide range of tasks. One of the best known methods for controlling redundancy is the null space projection, which assigns a priority while executing [...] Read more.
Redundant motion, which is possible when robotic manipulators are over-actuated, can be used to control robot arms for a wide range of tasks. One of the best known methods for controlling redundancy is the null space projection, which assigns a priority while executing desired tasks. However, when the manipulator is projected into null space, its motion would be limited, since the motion is only permitted in the direction that does not interfere with the primary task. In this study, we have analyzed the null space projector matrix to derive the appropriate direction of the redundant motion by quantifying the allowed motion in each direction. As a result, we have found an ellipsoidal boundary, in which the redundant motion is permitted to move. We have named this ellipsoidal boundary as ’null space quality’ in directions. The proposed null space quality shows similar aspects with that of the robot manipulability, but it reveals a decisively different value when the manipulator operates within the null space. The experimental results showed that the robotic manipulator tracked the sinusoidal input trajectory with reduced root mean square (RMS) error by 33.84%. Furthermore, we have demonstrated the obstacle avoidance of a robotic arm utilizing the null space projector while considering the null space quality. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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22 pages, 5434 KiB  
Article
Dynamic Modeling and Control of a Parallel Mechanism Used in the Propulsion System of a Biomimetic Underwater Vehicle
by Juan Antonio Algarín-Pinto, Luis E. Garza-Castañón, Adriana Vargas-Martínez and Luis I. Minchala-Ávila
Appl. Sci. 2021, 11(11), 4909; https://0-doi-org.brum.beds.ac.uk/10.3390/app11114909 - 27 May 2021
Cited by 5 | Viewed by 3123
Abstract
Incorporation of parallel mechanisms inside propulsion systems in biomimetic autonomous underwater vehicles (BAUVs) is a novel approach for motion generation. The vehicle to which the studied propulsion system is implemented presents thunniform locomotion, and its thrust depends mainly on the oscillation from its [...] Read more.
Incorporation of parallel mechanisms inside propulsion systems in biomimetic autonomous underwater vehicles (BAUVs) is a novel approach for motion generation. The vehicle to which the studied propulsion system is implemented presents thunniform locomotion, and its thrust depends mainly on the oscillation from its caudal fin. This paper describes the kinematic and dynamic modeling of a 3-DOF spherical 3UCU-1S parallel robotic system to which the caudal fin of a BAUV is attached. Lagrange formalism was employed for inverse dynamic modeling, and its derivation is detailed throughout this paper. Additionally, the implementation of control strategies to compute forces required to actuate limbs to change platform’s flapping frequencies was developed. Four controllers: classic PD, a feedforward plus feedback PD, an adaptive Fuzzy-PD, and a feedforward plus Fuzzy-PD were compared in different simulations. Results showed that augmenting oscillating frequencies (from 0.5 to 5 Hz) increased the complexity of the path tracking task, where the classic control strategy (i.e., PD) was not sufficient, reaching percentage errors above 9%. Control strategies using feedforward terms combined with adaptive feedback techniques reduced tracking error below 2% even during the presence of external disturbances. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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17 pages, 2996 KiB  
Article
Composite Error-Based Intelligent Adaptive Sliding Mode Control for Uncertain Bilaterally Symmetrical Hybrid Robot with Variational Desired Trajectories
by Qiuyue Qin and Guoqin Gao
Appl. Sci. 2021, 11(6), 2613; https://0-doi-org.brum.beds.ac.uk/10.3390/app11062613 - 15 Mar 2021
Viewed by 1266
Abstract
Some challenging issues exist in trajectory tracking control of an uncertain bilaterally symmetrical hybrid robot (UBSHR) with variational desired trajectories, mainly the uncertainty problem of UBSHR, the synchronization problem of UBSHR’s active joints and bilateral symmetrical hybrid mechanisms, and the flexible control problem [...] Read more.
Some challenging issues exist in trajectory tracking control of an uncertain bilaterally symmetrical hybrid robot (UBSHR) with variational desired trajectories, mainly the uncertainty problem of UBSHR, the synchronization problem of UBSHR’s active joints and bilateral symmetrical hybrid mechanisms, and the flexible control problem of active adaption to different technological requirements without artificially adjusting the control parameters or switching the hardware system. To solve these problems, an adaptive fuzzy neural network in conjunction with subtractive clustering algorithm (SC-AFNN) for UBSHR is proposed. More specifically, a novel composite error is incorporated into the second-order sliding mode control method to generate ideal training data samples and to improve the uncertain system robustness and synchronization performance simultaneously. Furthermore, the SC-AFNN is introduced to realize self-learning and self-adjusting of control rules and control parameters and to enhance the flexible control performance of UBSHR with variational desired trajectories. Strict theoretical proof of the defined errors’ relationship and the stability of the poposed control method is given. Ultimately, simulations and experiments for the prototype system of an UBSHR are conducted to verify the effectiveness of the proposed control method. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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16 pages, 4021 KiB  
Article
Research of Calibration Method for Industrial Robot Based on Error Model of Position
by Tianyan Chen, Jinsong Lin, Deyu Wu and Haibin Wu
Appl. Sci. 2021, 11(3), 1287; https://0-doi-org.brum.beds.ac.uk/10.3390/app11031287 - 31 Jan 2021
Cited by 17 | Viewed by 3746
Abstract
Based on the current situation of high precision and comparatively low APA (absolute positioning accuracy) in industrial robots, a calibration method to enhance the APA of industrial robots is proposed. In view of the "hidden" characteristics of the RBCS (robot base coordinate system) [...] Read more.
Based on the current situation of high precision and comparatively low APA (absolute positioning accuracy) in industrial robots, a calibration method to enhance the APA of industrial robots is proposed. In view of the "hidden" characteristics of the RBCS (robot base coordinate system) and the FCS (flange coordinate system) in the measurement process, a comparatively general measurement and calibration method of the RBCS and the FCS is proposed, and the source of the robot terminal position error is classified into three aspects: positioning error of industrial RBCS, kinematics parameter error of manipulator, and positioning error of industrial robot end FCS. The robot position error model is established, and the relation equation of the robot end position error and the industrial robot model parameter error is deduced. By solving the equation, the parameter error identification and the supplementary results are obtained, and the method of compensating the error by using the robot joint angle is realized. The Leica laser tracker is used to verify the calibration method on ABB IRB120 industrial robot. The experimental results show that the calibration method can effectively enhance the APA of the robot. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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Review

Jump to: Research

41 pages, 3103 KiB  
Review
Inertial Parameter Identification in Robotics: A Survey
by Quentin Leboutet, Julien Roux, Alexandre Janot, Julio Rogelio Guadarrama-Olvera and Gordon Cheng
Appl. Sci. 2021, 11(9), 4303; https://0-doi-org.brum.beds.ac.uk/10.3390/app11094303 - 10 May 2021
Cited by 31 | Viewed by 6460
Abstract
This work aims at reviewing, analyzing and comparing a range of state-of-the-art approaches to inertial parameter identification in the context of robotics. We introduce “BIRDy (Benchmark for Identification of Robot Dynamics)”, an open-source Matlab toolbox, allowing a systematic and formal performance assessment [...] Read more.
This work aims at reviewing, analyzing and comparing a range of state-of-the-art approaches to inertial parameter identification in the context of robotics. We introduce “BIRDy (Benchmark for Identification of Robot Dynamics)”, an open-source Matlab toolbox, allowing a systematic and formal performance assessment of the considered identification algorithms on either simulated or real serial robot manipulators. Seventeen of the most widely used approaches found in the scientific literature are implemented and compared to each other, namely: the Inverse Dynamic Identification Model with Ordinary, Weighted, Iteratively Reweighted and Total Least-Squares (IDIM-OLS, -WLS, -IRLS, -TLS); the Instrumental Variables method (IDIM-IV), the Maximum Likelihood (ML) method; the Direct and Inverse Dynamic Identification Model approach (DIDIM); the Closed-Loop Output Error (CLOE) method; the Closed-Loop Input Error (CLIE) method; the Direct Dynamic Identification Model with Nonlinear Kalman Filtering (DDIM-NKF), the Adaline Neural Network (AdaNN), the Hopfield-Tank Recurrent Neural Network (HTRNN) and eventually a set of Physically Consistent (PC-) methods allowing the enforcement of parameter physicality using Semi-Definite Programming, namely the PC-IDIM-OLS, -WLS, -IRLS, PC-IDIM-IV, and PC-DIDIM. BIRDy is robot-agnostic and features a complete inertial parameter identification pipeline, from the generation of symbolic kinematic and dynamic models to the identification process itself. This includes functionalities for excitation trajectory computation as well as the collection and pre-processing of experiment data. In this work, the proposed methods are first evaluated in simulation, following a Monte Carlo scheme on models of the 6-DoF TX40 and RV2SQ industrial manipulators, before being tested on the real robot platforms. The robustness, precision, computational efficiency and context of application the different methods are investigated and discussed. Full article
(This article belongs to the Special Issue Robots Dynamics: Application and Control)
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